Introduction

Analysis of MCF10A in 16 different conditions 2 biological replicates per sample

Quality check

Size factors and Dispersion plot

x
GM_none_1 1.0363804
IM_none_1 0.8394101
IM_none_2 1.0312687
IM_none_Glut_1 0.9116712
IM_none_Glut_2 1.0200687
IM_none_EGF_1 0.6409089
IM_none_EGF_2 1.0285384
IM_none_noIns_1 0.9494883
IM_none_noIns_2 1.0222049
IM_none_noGluc_1 1.0654041
IM_none_noGluc_2 0.8620713
IM_none_noHC_1 1.1827572
IM_none_noHC_2 1.0060447
IM_none_noCT_1 1.0396167
IM_none_noCT_2 1.0252612
IM_none_AMPKact_1 1.0266369
IM_none_AMPKact_2 1.1027958
IM_none_AKTinhib_1 1.0720796
IM_none_AKTinhib_2 1.1338035
IM_none_ERKinhib_1 1.0241596
IM_none_ERKinhib_2 1.1516436
IM_none_mTORC1inhib_1 1.0075421
IM_none_mTORC1inhib_2 1.1921120
IM_none_Oligo_1 0.6264784
IM_none_Oligo_2 1.0106023
IM_none_MPCinhib_1 1.1699916
IM_none_MPCinhib_2 0.9356112
IM_none_LDHinhib_1 1.0862708
IM_none_LDHinhib_2 1.0147222
IM_none_IL6_1 1.1514910
IM_none_IL6_2 1.0673677

PCA

All conditions

Better separation on that central cluster

Removal of - Oligomycin - EGF positive - Growth medium - IL6 - IM HC neg - IM ins neg

I think we can see a pretty evident batch effect per replicate!

Attempt to correct the batch effect

I think we can see a pretty evident batch effect per replicate!

Distance matrix

Look at the batch effect disappear

Same thing here, the batch effect can seen and disappears with the limma::removeBatchEffect function. Meaning I need to include replicates in the design formula.

Comparaisons of interest

What should we pick?

x
Intercept
condition_AKT_inhibitor_vs_IM
condition_AMPK_activator_vs_IM
condition_ERK_inhibitor_vs_IM
condition_Growth_Medium_vs_IM
condition_IL6_vs_IM
condition_IM_CT_neg_vs_IM
condition_IM_EGF_pos_vs_IM
condition_IM_Glucose_neg_vs_IM
condition_IM_Glutamine_pos_vs_IM
condition_IM_HC_neg_vs_IM
condition_IM_Ins_neg_vs_IM
condition_LDH_inhibitor_vs_IM
condition_MPC_inhibitor_vs_IM
condition_mTORC1_inhibitor_vs_IM
condition_Oligomycin_vs_IM
replicate

Maybe - Oligomycin vs IM - EGF vs IM - EGF vs Oligomycin

Oligomycin vs IM

Volcano plots

GSEA analysis (logFc)

GOBP

GOMF

Reactome

KEGG

Wikipathways

EGF vs IM

Volcano plot

GSEA analysis (logFc)

GOBP

GOMF

Reactome

KEGG

Wikipathways

Oligomycin vs EGF

x
Intercept
condition_IM_vs_IM_EGF_pos
condition_AKT_inhibitor_vs_IM_EGF_pos
condition_AMPK_activator_vs_IM_EGF_pos
condition_ERK_inhibitor_vs_IM_EGF_pos
condition_Growth_Medium_vs_IM_EGF_pos
condition_IL6_vs_IM_EGF_pos
condition_IM_CT_neg_vs_IM_EGF_pos
condition_IM_Glucose_neg_vs_IM_EGF_pos
condition_IM_Glutamine_pos_vs_IM_EGF_pos
condition_IM_HC_neg_vs_IM_EGF_pos
condition_IM_Ins_neg_vs_IM_EGF_pos
condition_LDH_inhibitor_vs_IM_EGF_pos
condition_MPC_inhibitor_vs_IM_EGF_pos
condition_mTORC1_inhibitor_vs_IM_EGF_pos
condition_Oligomycin_vs_IM_EGF_pos
replicate

Volcano plot

GSEA analysis (logFc)

GOBP

GOMF

Reactome

KEGG

Wikipathways

## R version 4.2.2 (2022-10-31 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19045)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=English_United States.utf8 
## [2] LC_CTYPE=English_United States.utf8   
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C                          
## [5] LC_TIME=English_United States.utf8    
## 
## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] clusterProfiler_4.6.0       msigdbr_7.5.1              
##  [3] xlsx_0.6.5                  pheatmap_1.0.12            
##  [5] ggrepel_0.9.2               biomaRt_2.54.1             
##  [7] cowplot_1.1.1               DESeq2_1.38.1              
##  [9] SummarizedExperiment_1.28.0 Biobase_2.58.0             
## [11] MatrixGenerics_1.10.0       matrixStats_0.62.0         
## [13] GenomicRanges_1.49.0        GenomeInfoDb_1.34.4        
## [15] IRanges_2.32.0              S4Vectors_0.36.0           
## [17] BiocGenerics_0.44.0         forcats_0.5.2              
## [19] stringr_1.4.1               dplyr_1.0.10               
## [21] purrr_0.3.5                 readr_2.1.3                
## [23] tidyr_1.2.1                 tibble_3.1.8               
## [25] ggplot2_3.4.0               tidyverse_1.3.2            
## [27] RColorBrewer_1.1-3         
## 
## loaded via a namespace (and not attached):
##   [1] utf8_1.2.2             tidyselect_1.2.0       RSQLite_2.2.19        
##   [4] AnnotationDbi_1.60.0   grid_4.2.2             BiocParallel_1.32.4   
##   [7] scatterpie_0.1.8       munsell_0.5.0          codetools_0.2-18      
##  [10] ragg_1.2.5             withr_2.5.0            colorspace_2.0-3      
##  [13] GOSemSim_2.24.0        filelock_1.0.2         highr_0.9             
##  [16] knitr_1.41             rstudioapi_0.14        rJava_1.0-6           
##  [19] DOSE_3.24.2            labeling_0.4.2         GenomeInfoDbData_1.2.9
##  [22] polyclip_1.10-4        bit64_4.0.5            farver_2.1.1          
##  [25] downloader_0.4         vctrs_0.5.0            treeio_1.22.0         
##  [28] generics_0.1.3         gson_0.0.9             xfun_0.34             
##  [31] timechange_0.1.1       BiocFileCache_2.6.1    R6_2.5.1              
##  [34] graphlayouts_0.8.4     locfit_1.5-9.6         bitops_1.0-7          
##  [37] cachem_1.0.6           fgsea_1.24.0           gridGraphics_0.5-1    
##  [40] DelayedArray_0.23.2    assertthat_0.2.1       scales_1.2.1          
##  [43] ggraph_2.1.0           enrichplot_1.18.3      googlesheets4_1.0.1   
##  [46] gtable_0.3.1           tidygraph_1.2.2        rlang_1.0.6           
##  [49] systemfonts_1.0.4      splines_4.2.2          lazyeval_0.2.2        
##  [52] gargle_1.2.1           broom_1.0.1            yaml_2.3.6            
##  [55] reshape2_1.4.4         modelr_0.1.10          backports_1.4.1       
##  [58] qvalue_2.30.0          tools_4.2.2            ggplotify_0.1.0       
##  [61] ellipsis_0.3.2         jquerylib_0.1.4        Rcpp_1.0.9            
##  [64] plyr_1.8.8             progress_1.2.2         zlibbioc_1.44.0       
##  [67] RCurl_1.98-1.9         prettyunits_1.1.1      viridis_0.6.2         
##  [70] haven_2.5.2            fs_1.5.2               magrittr_2.0.3        
##  [73] data.table_1.14.4      reprex_2.0.2           googledrive_2.0.0     
##  [76] ggnewscale_0.4.8       hms_1.1.2              xlsxjars_0.6.1        
##  [79] patchwork_1.1.2        evaluate_0.18          xtable_1.8-4          
##  [82] HDO.db_0.99.1          XML_3.99-0.13          readxl_1.4.1          
##  [85] gridExtra_2.3          compiler_4.2.2         crayon_1.5.2          
##  [88] shadowtext_0.1.2       htmltools_0.5.3        ggfun_0.0.9           
##  [91] tzdb_0.3.0             snow_0.4-4             geneplotter_1.76.0    
##  [94] aplot_0.1.9            lubridate_1.9.0        DBI_1.1.3             
##  [97] tweenr_2.0.2           dbplyr_2.2.1           MASS_7.3-58.1         
## [100] rappdirs_0.3.3         babelgene_22.9         Matrix_1.5-1          
## [103] cli_3.4.1              parallel_4.2.2         igraph_1.3.5          
## [106] pkgconfig_2.0.3        xml2_1.3.3             ggtree_3.6.2          
## [109] svglite_2.1.1          annotate_1.76.0        bslib_0.4.1           
## [112] XVector_0.38.0         rvest_1.0.3            yulab.utils_0.0.6     
## [115] digest_0.6.30          Biostrings_2.66.0      rmarkdown_2.18        
## [118] cellranger_1.1.0       fastmatch_1.1-3        tidytree_0.4.2        
## [121] curl_4.3.3             lifecycle_1.0.3        nlme_3.1-160          
## [124] jsonlite_1.8.3         viridisLite_0.4.1      limma_3.54.0          
## [127] fansi_1.0.3            pillar_1.8.1           lattice_0.20-45       
## [130] KEGGREST_1.38.0        fastmap_1.1.0          httr_1.4.4            
## [133] GO.db_3.16.0           glue_1.6.2             png_0.1-7             
## [136] bit_4.0.4              ggforce_0.4.1          stringi_1.7.8         
## [139] sass_0.4.2             blob_1.2.3             textshaping_0.3.6     
## [142] memoise_2.0.1          ape_5.6-2